Ransomware detection and mitigation using software-defined networking: The case of WannaCry. (June 2019)

• Record Type: Journal Article
• Authors: Akbanov, Maxat; Vassilakis, Vassilios G.; Logothetis, Michael D.
• Is Part Of: Computers & electrical engineering. Volume 76(2019)
• Page Start: 111
• Page End: 121
• Publication Date: 2019-06
• Subjects: WannaCry -- Ransomware -- Software-defined networking -- OpenFlow -- Malware analysis; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2019.03.012
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Modern day ransomware families implement sophisticated encryption and propagation schemes, thus limiting chances to recover the data almost to zero. We investigate the use of software-defined networking (SDN) to detect and mitigate advanced ransomware threat. We present our ransomware analysis results and our developed SDN-based security framework. For the proof of concept, the infamous WannaCry ransomware was used. Based on the obtained results, we design an SDN detection and mitigation framework and develop a solution based on OpenFlow. The developed solution detects suspicious activities through network traffic monitoring and blocks infected hosts by adding flow table entries into OpenFlow switches in a real-time manner. Finally, our experiments with multiple samples of WannaCry show that the developed mechanism in all cases is able to promptly detect the infected machines and prevent WannaCry from spreading.